PET-CT in radiotherapy for lung cancer

FAPI-74 PET/CT Using Either 18F-AlF or Cold-Kit 68Ga Labeling: Biodistribution, Radiation Dosimetry, and Tumor Delineation in Lung Cancer Patients

⁶⁸Ga-fibroblast activation protein inhibitors (FAPIs) 2, 4, and 46 have already been proposed as promising PET tracers. However, the short half-life of ⁶⁸Ga (68 min) creates problems with manufacture and delivery. ¹⁸F (half-life, 110 min) labeling would result in a more practical large-scale production, and a cold-kit formulation would improve the spontaneous availability. The NOTA chelator ligand FAPI-74 can be labeled with both ¹⁸F-AlF and ⁶⁸Ga. Here, we describe the in vivo evaluation of ¹⁸F-FAPI-74 and a proof of mechanism for ⁶⁸Ga-FAPI-74 labeled at ambient temperature. Methods: In 10 patients with lung cancer, PET scans were acquired at 10 min, 1 h, and 3 h after administration of 259 ± 26 MBq of ¹⁸F-FAPI-74. Physiologic biodistribution and tumor uptake were semiquantitatively evaluated on the basis of SUV at each time point. Absorbed doses were evaluated using OLINDA/EXM, version 1.1, and QDOSE dosimetry software with the dose calculator IDAC-Dose, version 2.1. Identical methods were used to evaluate one examination after injection of 263 MBq of ⁶⁸Ga-FAPI-74. Results: The highest contrast was achieved in primary tumors, lymph nodes, and distant metastases at 1 h after injection, with an SUV_max of more than 10. The effective dose per a 100-MBq administered activity of ¹⁸F-FAPI-74 was 1.4 ± 0.2 mSv, and for ⁶⁸Ga-FAPI-74 it was 1.6 mSv. Thus, the radiation burden of a diagnostic ¹⁸F-FAPI-74 PET scan is even lower than that of PET scans with ¹⁸F-FDG and other ¹⁸F tracers; ⁶⁸Ga-FAPI-74 is comparable to other ⁶⁸Ga ligands. FAPI PET/CT supported target volume definition for guiding radiotherapy. Conclusion: The high contrast and low radiation burden of FAPI-74 PET/CT favor multiple clinical applications. Centralized large-scale production of ¹⁸F-FAPI-74 or decentralized cold-kit labeling of ⁶⁸Ga-FAPI-74 allows flexible routine use.

Volumetric CT-based segmentation of NSCLC using 3D-Slicer

Accurate volumetric assessment in non-small cell lung cancer (NSCLC) is critical for adequately informing treatments. In this study we assessed the clinical relevance of a semiautomatic computed tomography (CT)-based segmentation method using the competitive region-growing based algorithm, implemented in the free and public available 3D-Slicer software platform. We compared the 3D-Slicer segmented volumes by three independent observers, who segmented the primary tumour of 20 NSCLC patients twice, to manual slice-by-slice delineations of five physicians. Furthermore, we compared all tumour contours to the macroscopic diameter of the tumour in pathology, considered as the "gold standard". The 3D-Slicer segmented volumes demonstrated high agreement (overlap fractions > 0.90), lower volume variability (p = 0.0003) and smaller uncertainty areas (p = 0.0002), compared to manual slice-by-slice delineations. Furthermore, 3D-Slicer segmentations showed a strong correlation to pathology (r = 0.89, 95%CI, 0.81-0.94). Our results show that semiautomatic 3D-Slicer segmentations can be used for accurate contouring and are more stable than manual delineations. Therefore, 3D-Slicer can be employed as a starting point for treatment decisions or for high-throughput data mining research, such as Radiomics, where manual delineating often represent a time-consuming bottleneck.

Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT

BACKGROUND

This study compared manually delineated gross tumour volume (GTV) and automatically generated biological tumour volume (BTV) based on fluoro-deoxy-glucose (FDG) positron emission tomography (PET)/CT to assess the robustness of predefined PET algorithms for radiotherapy (RT) planning in routine clinical practice.

METHODS

RT-planning data from 20 consecutive patients (lung- (40%), oesophageal- (25%), gynaecological- (25%) and colorectal (10%) cancer) who had undergone FDG-PET/CT planning between 08/2010 and 09/2011 were retrospectively analysed, five of them underwent neoadjuvant chemotherapy before radiotherapy. In addition to manual GTV contouring, automated segmentation algorithms were applied-among these 38%, 42%, 47% and 50% SUVmax as well as the PERCIST total lesion glycolysis (TLG) algorithm. Different ratios were calculated to assess the overlap of GTV and BTV including the conformity index and the ratio GTV included within the BTV.

RESULTS

Median age of the patients was 66 years and median tumour SUVmax 9.2. Median size of the GTVs defined by the radiation oncologist was 43.7 ml. Median conformity indices were between 30.0-37.8%. The highest amount of BTV within GTV was seen with the 38% SUVmax algorithm (49.0%), the lowest with 50% SUVmax (36.0%). Best agreement was obtained for oesophageal cancer patients with a conformity index of 56.4% and BTV within GTV ratio of 71.1%.

CONCLUSIONS

At present there is only low concordance between manually derived GTVs and automatically segmented FDG-PET/CT based BTVs indicating the need for further research in order to achieve higher volumetric conformity and therefore to get access to the full potential of FDG-PET/CT for optimization of radiotherapy planning.